Computational systems for biomedical data

• US 8,122,073 B2
• Filed: 05/31/2007
• Issued: 02/21/2012
• Est. Priority Date: 09/29/2006
• Status: Active Grant

• Current Assignee: Travera, LLC
• Original Assignee: The Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
• Inventors: Jung, Edward K. Y., Levien, Royce A., Lord, Robert W., Wood, Lowell L. Jr.
• Primary Examiner(s): Corrielus, Jean M
• Application Number:
  US11/809,776
• Publication Number:
  US 20080082503A1
• Time in Patent Office: 1,727 Days
• Field of Search: 707/10, 707/104.1, 707/3, 707/812, 707/954, 707/999.104, 707/999.003, 600/544, 600/300, 705/2, 705/3, 702/19, 702/20
• US Class Current: 707/999.003
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y10S 707/954 Relational
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

Methods, apparatuses, computer program products, devices and systems are described that accepting an input identifying a treatment target in search of an agent, the input associated with at least one query parameter; determining, based on the input, at least one subset of study data for which at least one adverse event profile associated with administration of at least one agent is acceptable within a defined limit relative to a population for which the at least one adverse event profile is unacceptable with respect to the defined limit; and presenting the agent, based on the at least one subset and the at least one query parameter.

Claims

1. A study data analysis system to identify agents associated with one or more treatment target which are associated with a specific subpopulation of individuals, said system comprising:

one or more system unit housing a memory and a microprocessor;

circuitry for accepting an input identifying a treatment target in search of an agent, the input associated with at least one query parameter;

circuitry for searching at least one dataset and extracting from the at least one dataset at least one subset of study data in response to said treatment target in search of said agent and said query parameter, wherein the circuitry for searching at least one dataset includes a circuitry that searches at least a Physicians'"'"' Desk Reference dataset; and

at least an Adverse Event Reporting System dataset, and wherein the circuitry for extracting from the at least one dataset at least one subset of study data in response to said treatment target in search of an agent and said query parameter includes a circuitry that extracts from the at least one dataset a subset characterized by one or more genetic parameters, epigenetic parameters, biochemical parameter, gene expression parameter, protein expression parameter, behavioral parameter, physiologic parameter, demographic parameter, adverse event parameter, age, gender, ethnicity, race, liver enzyme genotype, or medical history, lifestyle, exercise regimen, diet, nutritional regimen, dietary supplementation, concomitant medical therapy, or concomitant alternative medical therapy, linkage disequilibrium analysis profile, haplotype profile, single nucleotide polymorphism profile, or individual genetic sequence profile;

circuitry for including at least one subpopulation of the at least an subset for which at least one adverse event profile associated with administration of at least one agent is acceptable within a defined limit relative to a population for which the at least one adverse event profile is unacceptable with respect to the defined limit; and

circuitry for presenting the agent, based on the at least one subset and the at least one query parameter.

2. The system of claim 1 wherein the circuitry for extracting from the at least one dataset at least one subset of study data in response to said treatment target in search of an agent and said query parameter comprises:

circuitry that extracts from the at least one dataset a subset having a significantly lower incidence of at least one adverse event than that of at least one reported clinical trial for the at least one agent as the at least one subset.

3. The system of claim 1 wherein the circuitry for extracting from the at least one dataset at least one subset of study data in response to said treatment target in search of an agent and said query parameter comprises:

circuitry that extracts from the at least one dataset at least one subset having at least a defined level of efficacy in treating the at least one treatment target as the at least one subset.

4. The system of claim 1 further comprising:

circuitry that correlates the at least one subset with subpopulation identifier data.

5. The system of claim 4 wherein the circuitry for correlating the at least one subset of study data with subpopulation identifier data comprises:

circuitry that correlates the at least one subset with at least one of genetic data, epigenetic data, biochemical data, gene expression data, protein expression data, behavioral data, physiologic data, or demographic data as the subpopulation identifier data.

6. The system of claim 4 wherein the circuitry for correlating the at least one subset of study data with subpopulation identifier data comprises:

circuitry that correlates the at least one subset with at least one of age data, gender data, ethnicity data, race data, liver enzyme genotype data, or medical history data as the subpopulation identifier data.

7. The system of claim 4 wherein the circuitry for correlating the at least one subset of study data with subpopulation identifier data comprises:

circuitry that correlates the at least one subset with at least one of lifestyle data, exercise regimen data, diet data, nutritional regimen data, dietary supplementation data, concomitant medical therapy data, or concomitant alternative medical therapy data as the subpopulation identifier data.

8. The system of claim 4 wherein the circuitry for correlating the at least one subset of study data with subpopulation identifier data comprises:

circuitry that correlates the at least one subset with at least one of linkage disequilibrium analysis data, haplotype data, single nucleotide polymorphism data, or individual genetic sequence data as the subpopulation identifier data.